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机器学习工程师实习生 - 2027年入职

雇主

TikTok

地点

California · San Jose · 美国

待遇

$面议

工作模式

线下

截止日期

1月8日

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岗位摘要

Machine Learning Engineer Intern to develop large-scale Ads systems and applied ML projects for TikT

岗位职责

Global Monetization Productand Technology teams are building the next-generation monetization platforms to help millions of customers grow their businesses, utilizing our products like TikTok.
Our team develops a wide variety of advertisements for numerous uses including feeds, live streaming, branding, measurement, targeting, search, vertical solutions, creative solutions, and business integrity.
We are looking for talented individuals to join us for an internship.
PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.
Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis, so we encourage you to apply early.
Please clearly state your availability in your resume (Start date, End date).
What is the General Hire?
If you're applying under the General HIre track for the GMPT-Performance Monetization organization, your resume will be reviewed by all the subteams, and we'll help identify one or more teams that are the best match for you.
Why General Hire?
This process gives you broader exposure and increases your chances of finding the right team fit!
Responsibilities:
- Participate in the development of a large-scale Ads system.
- Responsible for the development of state-of-the-art applied machine learning projects.
- Own key targeting components or strategies in the TikTok ads monetization ecosystem.
- Work with product and business teams on product vision.

申请条件

PhD student. Availability to start in 2027. Must clearly state availability (start date, end date) in resume.

雇主简介

TikTok is a leading short-form video platform that develops core training and serving infrastructure for large-scale recommendation systems and AI infrastructure for foundation models and LLMs.

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数据来源:TikTok

岗位信息来源于公开渠道,版权归原作者所有